Trait-based random generation
Generation of random graphs based on different vertex types.
sample_pref(nodes, types, type.dist = rep(1, types), fixed.sizes = FALSE, pref.matrix = matrix(1, types, types), directed = FALSE, loops = FALSE)
sample_asym_pref(nodes, types, type.dist.matrix = matrix(1, types, types), pref.matrix = matrix(1, types, types), loops = FALSE)
- The number of vertices in the graphs.
- The number of different vertex types.
- The distribution of the vertex types, a numeric vector of
typescontaining non-negative numbers. The vector will be normed to obtain probabilities.
- Fix the number of vertices with a given vertex type
type.distargument gives the group sizes (i.e. number of vertices with the different labels) in this case.
- A square matrix giving the preferences of the vertex
types. The matrix has
typesrows and columns.
- Logical constant, whether to create a directed graph.
- Logical constant, whether self-loops are allowed in the graph.
- Passed to the constructor,
- The joint distribution of the in- and out-vertex types.
Both models generate random graphs with given vertex types. For
sample_pref the probability that two vertices will be connected
depends on their type and is given by the
sample_asym_pref each vertex has an in-type and an
out-type and a directed graph is created. The probability that a directed
edge is realized from a vertex with a given out-type to a vertex with a
given in-type is given in the
- An igraph graph.
pf <- matrix( c(1, 0, 0, 1), nr=2) g <- sample_pref(20, 2, pref.matrix=pf) tkplot(g, layout=layout_with_fr) pf <- matrix( c(0, 1, 0, 0), nr=2) g <- sample_asym_pref(20, 2, pref.matrix=pf) tkplot(g, layout=layout_in_circle)